Find the robust nodes in ALPACA community using CRANE

Usage

alpacaCrane(input, alp, alpha = 0.1, beta = 0, iteration = 30, isParallel = F)

input: same input for alpaca: first column TF, second column Genes, third column edge weights from baseline condition, fourth column edge weights from disease condition.
alp: alpca object in list format (output from alpaca package)
alpha: alpha paramter perturbs each edge weights
beta: beta parameter perturbs the strength of each node. Set this to 0 if you want nodes to have node strength identical to the orignal network.
iteration: Number of CRANE distributions to create. Higher value leads to better ranking but longer runtime.
isParallel: TRUE = use Multithread / FALSE = do not use Multithread

list of data frames

if (FALSE) {

input=cbind(nonAng,ang[,3])
alp=alpaca(input,NULL,verbose = F)
alpListObject=alpacaCrane(input, alp, isParallel = T)

}